Improving Radar Imaging with Computational Imaging and Novel Antenna Desig

Traditional radar imaging systems are implemented using the focal plane technique, steering beam antennas, or synthetic aperture imaging. These conventional methods require either a large number of sensors to form a focal plane array similar to the idea of an optical camera, or a single transceiver mechanically scanning the field of view. The former results in expensive systems whereas the latter results in long acquisition time. Computational imaging methods are widely used for the ability to acquire information beyond the recorded pixels, thus are ideal options for reducing the number of radar sensors in radar imaging systems. Novel antenna designs such as the frequency diverse antennas are capable of optimizing antennas for computational imaging algorithms. This thesis tries to find a solution for improving the efficiency of radar imaging using a method that combines computational imaging and novel antenna designs. This thesis first proposes two solutions to improve the two aspects of the tradeoff respectively, i.e. the number of sensors and mechanical scanning. A method using time-of-flight imaging algorithm with a sparse array of antennas is proposed as a solution to reduce the number of sensors required to estimate a reflective surface. An adaptive algorithm based on the Bayesian compressive sensing framework is proposed as a solution to minimize mechanical scanning for synthetic aperture imaging systems. The thesis then explores the feasibility to further improve radar imaging systems by combining computational imaging and antenna design methods as a solution. A rapid prototyping method for manufacturing custom-designed antennas is developed for implementing antenna designs quickly in a laboratory environment. This method has facilitated the design of a frequency diverse antenna based on a leaky waveguide design, which can be used under computational imaging framework to perform 3D imaging. The proposed system is capable of performing imaging and target localization using only one antenna and without mechanical scanning, thus is a promising solution to ultimately improve the efficiency for radar imaging.